Literature DB >> 21702771

A memory-based theory of verbal cognition.

Simon Dennis1.   

Abstract

The syntagmatic paradigmatic model is a distributed, memory-based account of verbal processing. Built on a Bayesian interpretation of string edit theory, it characterizes the control of verbal cognition as the retrieval of sets of syntagmatic and paradigmatic constraints from sequential and relational long-term memory and the resolution of these constraints in working memory. Lexical information is extracted directly from text using a version of the expectation maximization algorithm. In this article, the model is described and then illustrated on a number of phenomena, including sentence processing, semantic categorization and rating, short-term serial recall, and analogical and logical inference. Subsequently, the model is used to answer questions about a corpus of tennis news articles taken from the Internet. The model's success demonstrates that it is possible to extract propositional information from naturally occurring text without employing a grammar, defining a set of heuristics, or specifying a priori a set of semantic roles. 2005 Lawrence Erlbaum Associates, Inc.

Year:  2005        PMID: 21702771     DOI: 10.1207/s15516709cog0000_9

Source DB:  PubMed          Journal:  Cogn Sci        ISSN: 0364-0213


  5 in total

1.  Constructing semantic representations from a gradually-changing representation of temporal context.

Authors:  Marc W Howard; Karthik H Shankar; Udaya K K Jagadisan
Journal:  Top Cogn Sci       Date:  2011-01

2.  An associative account of the development of word learning.

Authors:  Vladimir M Sloutsky; Hyungwook Yim; Xin Yao; Simon Dennis
Journal:  Cogn Psychol       Date:  2017-06-20       Impact factor: 3.468

3.  Retrieved context and the discovery of semantic structure.

Authors:  Vinayak A Rao; Marc W Howard
Journal:  Adv Neural Inf Process Syst       Date:  2008

4.  Scale-Dependent Relationships in Natural Language.

Authors:  Aakash Sarkar; Marc W Howard
Journal:  Comput Brain Behav       Date:  2021-01-04

5.  Encoding sequential information in semantic space models: comparing holographic reduced representation and random permutation.

Authors:  Gabriel Recchia; Magnus Sahlgren; Pentti Kanerva; Michael N Jones
Journal:  Comput Intell Neurosci       Date:  2015-04-07
  5 in total

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